Memorability of Enhanced Informational Graphics The effects of design relevance and chart type on recall

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Alyssa Peña
Eric Ragan
Lane Harrison


Design enhancements are often added to charts, signage, and infographics to help garner attention or communicate a message. Though it is argued that they may also detract user’s focus on the underlying information, prior studies have contributed evidence that visual design enhancements and even simple decorations can improve memory of visual displays. However, there is limited empirical knowledge about how the type of aesthetic enhancements infuences memory, and what informational and data elements are remembered from a visualization. We conducted a user study testing chart types (line, pie, and bar), the presence of color, and whether added enhancements were contextually related to the data topic presented in each chart. We found that enhancements relevant to the data helped in the recall of title and thematic elements, but enhancements did not signifcantly affect recall of specifc data values. This suggests that using relevant enhancements can have a positive effect on memorability of some chart content, but only if the design styles are chosen well to match the information topic. Recall of chart topics for unrelated embellishments was worse than plain, un-enhanced charts, which suggests that visual enhancement can distract or interfere with memorability if the viewer does not understand a meaningful connection between informational topic and design modifcations.

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Atkinson, R.C. and Shiffrin, R.M. (1968). Human memory: A proposed system and its control processes. Psychology of Learning and Motivation 2, 89–195.

Bateman, S., Mandryk, R.L., Gutwin, C., Genest, A., McDine, D. and Brooks, C. (2010). Useful junk?: The effects of visual embellishment on comprehension and memorability of charts. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2573–2582.

Beecham, R., Dykes, J., Meulemans, W., Slingsby, A., Turkay, C. and Wood, J. (2017). Map Line Ups: Effects of spatial structure on graphical inference. IEEE Transactions on Visualization and Computer Graphics 23(1), 391–400.

Borgo, R., Abdul-Rahman, A., Mohamed, F., Grant, P.W., Reppa, I., Floridi, L. and Chen, M. (2012). An empirical study on using visual embellishments in visualization. IEEE Transactions on Visualization & Computer Graphics 18, 2759–2768.

Borkin, M.A., Bylinskii, Z., Kim, N.W., Bainbridge, C.M., Yeh, C.S., Borkin, D., Pfister, H. and Oliva, A. (2016). Beyond memorability: Visualization recognition and recall. IEEE Transactions on Visualization and Computer Graphics 22(1), 519–528.

Borkin, M.A., Vo, A.A., Bylinskii, Z., Isola, P., Sunkavalli, S., Oliva, A. and Pfister, H. (2013). What makes a visualization memorable? IEEE Transactions on Visualization and Computer Graphics 19(12), 2306–2315.

Bylinskii, Z., Kim, N.W., O’Donovan, P., Alsheikh, S., Madan, S., Pfister, H., Durand, F., Russell, B. and Hertzmann, A. (2017). Learning visual importance for graphic designs and data visualizations. Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, 57–69.

Chase, W.G. and Simon, H.A. (1973). Perception in chess. Cognitive Psychology 4(1), 55–81.

Claes, S. and Vande Moere, A. (2013). Street infographics: Raising awareness of local issues through a situated urban visualization. Proceedings of the 2nd ACM International Symposium on Pervasive Displays, 133–138.

Cleveland, W.S. and McGill, R. (1984). Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association 79(387), 531–554.

Correll, M. and Heer, J. (2017a). “Black hat visualization.” Paper presented at DECISIVe Workshop, IEEE VIS 2017, Phoenix, Oct 2.

Correll, M. and Heer, J. (2017b). Regression by Eye: Estimating Trends in Bivariate Visualizations. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 1387–1396.

Craik, F. I. and Tulving, E. (1975). Depth of processing and the retention of words in episodic memory. Journal of Experimental Psychology: General 104(3), 268.

Few, S. (2011). “The chartjunk debate: A close examination of recent findings.” Perceptual Edge, April/May/June 2011.

Haroz, S., Kosara, R. and Franconeri, S.L. (2015). Isotype visualization: Working memory, performance, and engagement with pictographs Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 1191–1200.

Harrison, L., Yang, F., Franconeri, S. and Chang, R. (2014). Ranking Visualizations of Correlation Using Weber’s Law. IEEE Transactions on Visualization and Computer Graphics 20(12), 1943–1952.

Heer, J. and Bostock, M. (2010). Crowdsourcing graphical perception: Using mechanical turk to assess visualization design. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 203–212.

Holmes, N. (1984). Designer’s guide to creating charts & diagrams. New York: Watson-Guptill.

Jardine, N., Ondov, B.D., Elmqvist, N. and Franconeri, S. (2019). The Perceptual Proxies of Visual Comparison. IEEE Transactions on Visualization and Computer Graphics 26(1), 1012–1021.

Kellaris, J.J. and Machleit, K.A. (2016). Signage as Marketing Communication: A Conceptual Model and Research Propositions. Interdisciplinary Journal of Signage and Wayfinding 1(1).

Kim, N., Schweickart, E., Liu, Z., Dontcheva, M., Li, W., Popovic, J. and Pfister, H. (2018). Data-driven guides: Supporting expressive design for information graphics. IEEE Transactions on Visualization & Computer Graphics 23(1), 491-500.

Kosara, R. (2007). Visualization criticism: The missing link between information visualization and art. 11th International Conference Information Visualization, 631–636.

Lahrache, S., El Ouazzani, R. and El Qadi, A. (2018). Visualizations memorability through visual attention and image features. Procedia Computer Science 127, 328–335.

Li, H. and Moacdieh, N. (2014). Is “chart junk” useful? An extended examination of visual embellishment. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 58(1), 1516–1520.

Lin, S., Fortuna, J., Kulkarni, C., Stone, M. and Heer, J. (2013). Selecting semantically-resonant colors for data visualization. Computer Graphics Forum 32, 401–410.

Liu, Z., Thompson, J., Wilson, A., Dontcheva, M., Delorey, J., Grigg, S., Kerr, B. and Stasko, J. (2018). Data Illustrator: Augmenting Vector Design Tools with Lazy Data Binding for Expressive Visualization Authoring. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems.

Nuthall, G. (2000). The role of memory in the acquisition and retention of knowledge in science and social studies units. Cognition and Instruction 18(1), 83–139.

Pandey, A.V., Rall, K., Satterthwaite, M.L., Nov, O. and Bertini, E. (2015). How deceptive are deceptive visualizations?: An empirical analysis of common distortion techniques. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 1469–1478.

Quispel, A., Maes, A. and Schilperoord, J. (2016). Graph and chart aesthetics for experts and laymen in design: The role of familiarity and perceived ease of use. Information Visualization 15(3), 238–252.

Ren, D., Lee, B. and Brehmer, M. (2018). Charticulator: Interactive Construction of Bespoke Chart Layouts. IEEE Transactions on Visualization and Computer Graphics 25(1), 789-799.

Rensink, R.A. and Baldridge, G. (2010). The perception of correlation in scatterplots. Computer Graphics Forum 29, 1203–1210.

Ritchie, D, and Karge, B.D. (1996). Making information memorable: Enhanced knowledge retention and recall through the elaboration process. Preventing School Failure: Alternative Education for Children and Youth 41(1), 28–33.

Ruchikachorn, P. and Mueller, K. (2015). Learning visualizations by analogy: Promoting visual literacy through visualization morphing. IEEE Transactions on Visualization and Computer Graphics 21(9), 1028–1044.

Saket, B., Srinivasan, A., Ragan, E.D. and Endert, A. (2018). Evaluating interactive graphical encodings for data visualization. IEEE Transactions on Visualization and Computer Graphics 24(3), 1316–1330.

Skog, T., Ljungblad, S. and Holmquist, L. E. (2003). Between aesthetics and utility: Designing ambient information visualizations. IEEE Symposium on Information Visualization, 233–240.

Smith, D.A. and Graesser, A.C. (1981). Memory for actions in scripted activities as a function of typicality, retention interval, and retrieval task. Memory & Cognition 9(6), 550–559.

Szafir, D.A. (2017). Modeling Color Difference for Visualization Design. IEEE Transactions on Visualization and Computer Graphics 24(1), 392-401.

Tufte, E. (1983). The visual display of quantitative information. Cheshire: Graphics Press.

Wickham, H., Cook, D., Hofmann, H. and Buja, A. (2010). Graphical inference for infovis. IEEE Transactions on Visualization and Computer Graphics 16(6), 973–979.

Xia, H., Henry Riche, N., Chevalier, F., De Araujo, B. and Wigdor, D. (2018). DataInk: Direct and Creative Data-Oriented Drawing. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems.

Zacks, J., Levy, E., Tversky, B. and Schiano, D.J. (1998). Reading bar graphs: Effects of extraneous depth cues and graphical context. Journal of Experimental Psychology: Applied 4(2), 119.